Acalabrutinib as a novel hope for the treatment of breast and lung cancer: an in-silico proof of concept

Drug repurposing is proved to be a groundbreaking concept in the field of cancer research, accelerating the pace of de novo drug discovery by investigating the anti-cancer activity of the already approved drugs. On the other hand, it got highly benefitted from the advancement in the in-silico tools and techniques, which are used to build up the initial "proof of concept" based on the drug-target interaction. Acalabrutinib (ACL) is a well-known drug for the treatment of hematological malignancies. But, the therapeutic ability of ACL against solid tumors is still unexplored. Thereby, the activity of ACL on breast cancer and lung cancer was evaluated utilizing different computational methods. A series of proteins such as VEGFR1, ALK, BCL2, CXCR-4, mTOR, AKT, PI3K, HER-2, and Estrogen receptors were selected based on their involvement in the progression of the breast as well as lung cancer. A multi-level computational study starting from protein-ligand docking to molecular dynamic (MD) simulations were performed to detect the binding potential of ACL towards the selected proteins. Results of the study led to the identification of ACL as a ligand that showed a high docking score and binding energy with HER-2, mTOR, and VEGFR-1 successively. Whereas, the MD simulations study has also shown good docked complex stability of ACL with HER2 and VEGFR1. Our findings suggest that interaction with those receptors can lead to preventive action on both breast and lung cancer, thus it can be concluded that ACL could be a potential molecule for the same purpose.Communicated by Ramaswamy H. Sarma.

Investigation of Potential Drug Targets for Cholesterol Regulation to Treat Alzheimer's Disease

Despite extensive research and seven approved drugs, the complex interplay of genes, proteins, and pathways in Alzheimer's disease remains a challenge. This implies the intricacies of the mechanism for Alzheimer's disease, which involves the interaction of hundreds of genes, proteins, and pathways. While the major hallmarks of Alzheimer's disease are the accumulation of amyloid plaques and tau protein tangles, excessive accumulation of cholesterol is reportedly correlated with Alzheimer's disease patients. In this work, protein-protein interaction analysis was conducted based upon the genes from a clinical database to identify the top protein targets with most data-indicated involvement in Alzheimer's disease, which include ABCA1, CYP46A1, BACE1, TREM2, GSK3B, and SREBP2. The reactions and pathways associated with these genes were thoroughly studied for their roles in regulating brain cholesterol biosynthesis, amyloid beta accumulation, and tau protein tangle formation. Existing clinical trials for each protein target were also investigated. The research indicated that the inhibition of SREBP2, BACE1, or GSK3B is beneficial to reduce cholesterol and amyloid beta accumulation, while the activation of ABCA1, CYP46A1, or TREM2 has similar effects. In this study, Sterol Regulatory Element-Binding Protein 2 (SREBP2) emerged as the primary protein target. SREBP2 serves a pivotal role in maintaining cholesterol balance, acting as a transcription factor that controls the expression of several enzymes pivotal for cholesterol biosynthesis. Novel studies suggest that SREBP2 performs a multifaceted role in Alzheimer's disease. The hyperactivity of SREBP2 may lead to heightened cholesterol biosynthesis, which suggested association with the pathogenesis of Alzheimer's disease. Lowering SREBP2 levels in an Alzheimer's disease mouse model results in reduced production of amyloid-beta, a major contributor to Alzheimer's disease progression. Moreover, its thoroughly analyzed crystal structure allows for computer-aided screening of potential inhibitors; SREBP2 is thus selected as a prospective drug target. While more protein targets can be added onto the list in the future, this work provides an overview of key proteins involved in the regulation of brain cholesterol biosynthesis that may be further investigated for Alzheimer's disease intervention.

Sarcorucinine-D Inhibits Cholinesterases and Calcium Channels: Molecular Dynamics Simulation and In Vitro Mechanistic Investigations

Acetylcholinesterase (AChE) inhibitors and calcium channel blockers are considered effective therapies for Alzheimer’s disease. AChE plays an essential role in the nervous system by catalyzing the hydrolysis of the neurotransmitter acetylcholine. In this study, the inhibition of the enzyme AChE by Sarcorucinine-D, a pregnane type steroidal alkaloid, was investigated with experimental enzyme kinetics and molecular dynamics (MD) simulation techniques. Kinetics studies showed that Sarcorucinine-D inhibits two cholinesterases—AChE and butyrylcholinesterase (BChE)—noncompetitively, with K_i values of 103.3 and 4.66 µM, respectively. In silico ligand-protein docking and MD simulation studies conducted on AChE predicted that Sarcorucinine-D interacted via hydrophobic interactions and hydrogen bonds with the residues of the active-site gorge of AChE. Sarcorucinine-D was able to relax contractility concentration-dependently in the intestinal smooth muscles of jejunum obtained from rabbits. Not only was the spontaneous spasmogenicity inhibited, but it also suppressed K⁺-mediated spasmogenicity, indicating an effect via the inhibition of voltage-dependent Ca²⁺ channels. Sarcorucinine-D could be considered a potential lead molecule based on its properties as a noncompetitive AChE inhibitor and a Ca²⁺ channel blocker.

Potential inhibitors for the novel coronavirus (SARS-CoV-2)

The lack of a vaccine or any effective treatment for the aggressive novel coronavirus disease (COVID-19) has created a sense of urgency for the discovery of effective drugs. Several repurposing pharmaceutical candidates have been reported or envisaged to inhibit the emerging infections of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), but their binding sites, binding affinities and inhibitory mechanisms are still unavailable. In this study, we use the ligand-protein docking program and molecular dynamic simulation to ab initio investigate the binding mechanism and inhibitory ability of seven clinically approved drugs (Chloroquine, Hydroxychloroquine, Remdesivir, Ritonavir, Beclabuvir, Indinavir and Favipiravir) and a recently designed α-ketoamide inhibitor (13b) at the molecular level. The results suggest that Chloroquine has the strongest binding affinity with 3CL hydrolase (Mpro) among clinically approved drugs, indicating its effective inhibitory ability for SARS-CoV-2. However, the newly designed inhibitor 13b shows potentially improved inhibition efficiency with larger binding energy compared with Chloroquine. We further calculate the important binding site residues at the active site and demonstrate that the MET 165 and HIE 163 contribute the most for 13b, while the MET 165 and GLN 189 for Chloroquine, based on residual energy decomposition analysis. The proposed work offers a higher research priority for 13b to treat the infection of SARS-CoV-2 and provides theoretical basis for further design of effective drug molecules with stronger inhibition.

Study on the Anti-Tumor Mechanism and Target of Triptolide based on Network Pharmacology and Molecular Docking

BACKGROUND

According to the special physiological and pharmacological activities of natural compounds, many drugs with special therapeutic effects have been developed. The triptolide (TP) is a kind of natural anti-tumor drug with a world patent, but its target and mechanism are yet not known.

OBJECTIVE

The study aims to explore and predict the target and mechanism of TP on non-small cell lung cancer (NSCLC), pancreatic cancer (PC) and colorectal cancer (CC) through network pharmacology technology.

METHODS

We screened the core targets of TP with NSCLC, PC and CC, respectively, and carried out network analysis, enrichment analysis and ligand-receptor docking to clarify its potential pharmacological mechanism.

RESULTS

By screening the core genes between TP with NSCLC, PC and CC, respectively, it was found that PTGS2 was the common target gene in the three cancers. NSCLC, CCL2, IL6, HMOX1 and COL1A1 are the specific target genes, while MMP2, JUN, and CXCL8 are the specific target genes in PC. In CC, the specific target genes includeERBB2, VEGFA, STAT1 andMAPK8. In enrichment analysis, it was found that the NF- κB, toll-like receptors and IL-17 signaling pathway were mainly involved in TP for these cancers. The binding energy of TP to the core target is less than that of cyclophosphamide.

CONCLUSIONS

This study preliminarily revealed that TP may prevent and treat cancers\ through multiple targets and pathways. The possible mechanisms of TP include regulating immune and inflammatory responses, promoting apoptosis and inhibiting tumor development. It shows that TP may have a potential in treating kinds of tumors.

A Pilot Study of All-Computational Drug Design Protocol-From Structure Prediction to Interaction Analysis

Speeding up the drug discovery process is of great significance. To achieve that, high-efficiency methods should be exploited. The conventional wet-bench methods hardly meet the high-speed demand due to time-consuming experiments. Conversely, in silico approaches are much more efficient for drug discovery and design. However, in silico approaches usually serve as a supportive role in research processes. To fully exert the strength of computational methods, we propose a protocol which integrates various in silico approaches, from de novo protein structure prediction to ligand-protein interaction simulation. As a proof of concept, human SK2/calmodulin complex was used as a target for validation. First, we obtained a predicted structure of SK2/calmodulin and predicted binding sites which were consistent with the literature data. Then we investigated the ligand-protein interaction via virtual mutagenesis, flexible docking, and binding affinity calculation. As a result, the binding energies of mutants have similar trends compared with the EC₅₀ values (R = 0.6 for NS309 in V481 mutants). The results indicate that our protocol can be applied to the drug design of structure unknown proteins. Our study also demonstrates that the integration of in silico approaches is feasible and it facilitates the acceleration of new drug discovery.